Machine Learning Engineer: Imitation and Reinforcement Learning for Robotics
San Francisco, CA · San Francisco, California, United States
- Pay
- Pay not listedSimilar roles state $165K–$240K
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Engineering › Behavior — team source
Department: Engineering › Behavior
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require visa sponsorship to work in the United States?
From the employer’s application form
What you’ll work on
Full postingDesign, train, validate, and launch behavior cloning and reinforcement learning models
Build and maintain data ingestion, labeling, and management pipelines
Build metrics to evaluate models in open loop, simulation, and the real world
Integrate ML models into real-world autonomous systems with simulation and infrastructure teams
Deploy and debug models on hardware, handling latency and system integration issues
From the employer’s posting
Design, train, validate, and launch models for behavior cloning and reinforcement learning
Build and maintain data ingestion, labeling, and management pipelines
Build metrics to evaluate model performance in open loop, simulation, and in the real world
Collaborate with simulation, systems, and infrastructure teams to integrate ML models into real-world autonomous systems
Deploy and debug these models in real-world environments, addressing practical issues such as latency, hardware constraints, and system integration
Tools in this posting
- PyTorch
- TensorFlow
Source — Tool mentions in context
What We’re Looking For: - 3+ years of practical experience applying Machine Learning with Deep Learning frameworks, such as PyTorch/Tensorflow/JAX to solve real-world problems - 3+ years of professional experience building, deploying, and maintaining Machine Learning models in production environments
Posting record
Report an errorOpen 4 monthsWe first saw this posting 149 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026 · 149 days ago
- Recorded sightings
- 102
- Last seen by us
- Oct 29, 2026
- Employer says posted
- Jan 31, 2026
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Job description
Join the team bringing autonomy to the built world
At Bedrock, we're moving AI out of the lab and onto real job sites. Our team includes veterans who helped launch Waymo, scaled Segment to a $3.2B acquisition, and grew Uber Freight to $5B in revenue. We retrofit the heavy equipment contractors already own, starting with excavators, so experienced crews can safely take on more projects and deliver more of the critical infrastructure our society needs.
In August 2026, Bedrock-equipped excavators began doing fully autonomous, paid work on live commercial job sites. We've more than doubled our customer base since 2025, and our machines now work with contractors across the South, Midwest, and Mid-Atlantic
In October 2026, we raised a $600M Series C co-led by CapitalG and Emergence Capital, bringing our total funding to nearly $1B. We're using it to put more autonomous machines to work, build the field and operations teams behind every deployment, and expand into new machine types and job-site tasks.
This is where algorithms meet steel-toed boots. You'll work alongside construction veterans and world-class engineers to solve physical-world problems that simulations can't touch. If you're ready to do meaningful work on hard problems, we'd love to have you join us.
The Mission:
We’re looking for a Machine Learning Engineer with a focus on behavior learning, specifically data-driven behavior policies and robust data infrastructure. In this role, you'll be responsible for developing and scaling state-of-the-art learning architectures, while also building the data systems that make these models reliable, scalable, and reproducible in production.
What You’ll Do:
Design, train, validate, and launch models for behavior cloning and reinforcement learning
Build and maintain data ingestion, labeling, and management pipelines to ensure high-quality training datasets
Build metrics to evaluate model performance in open loop, simulation, and in the real world
Collaborate with simulation, systems, and infrastructure teams to integrate ML models into real-world autonomous systems
Deploy and debug these models in real-world environments, addressing practical issues such as latency, hardware constraints, and system integration
What We’re Looking For:
3+ years of practical experience applying Machine Learning with Deep Learning frameworks, such as PyTorch/Tensorflow/JAX to solve real-world problems
3+ years of professional experience building, deploying, and maintaining Machine Learning models in production environments
Familiarity with recent literature and methods in learned behavior policies
Practical experience in behavior cloning and/or reinforcement learning
Bonus: Experience with diffusion policies, Vision-Language-Action (VLA) models, or related technologies
Bonus: Published work in conferences such as ICRA, IROS, CoRL, CVPR, ECCV, ICCV, ICML, NeurIPS, …
Bedrock Robotics is an Equal Opportunity Employer
We’re committed to building a diverse and inclusive workplace. We consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, ancestry, age, disability, veteran status, genetic information, or any other protected characteristic.
Reasonable Accommodations
We want our hiring process to be accessible to everyone. If you need an accommodation to participate in the application or interview process, please let your recruiter know so we can support you.
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- Pay
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- Location & working pattern
San Francisco, California, United States
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